Scientific Critical Thinking
weapp-tailwindcss/weapp-tailwindcss
Evaluate research rigor. An agent skill from weapp-tailwindcss/weapp-tailwindcss.
Generates randomization sequences for RCTs including simple, blocked, and stratified allocation.
Install Randomization Gen
$ npx skills add aipoch/medical-research-skills --skill randomization-gen -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aipoch/medical-research-skills randomization-gen --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'scientific-skills/Protocol Design/randomization-gen' .claude/skills/randomization-gen && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "randomization-gen" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Protocol%20Design/randomization-gen into .claude/skills/randomization-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "randomization-gen", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Protocol%20Design/randomization-genType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aipoch/medical-research-skills --skill randomization-gen -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aipoch/medical-research-skills randomization-gen --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/'scientific-skills/Protocol Design/randomization-gen' .agents/skills/randomization-gen && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "randomization-gen" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Protocol%20Design/randomization-gen into .agents/skills/randomization-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "randomization-gen", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aipoch/medical-research-skills --skill randomization-gen -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aipoch/medical-research-skills randomization-gen --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/'scientific-skills/Protocol Design/randomization-gen' .cursor/skills/randomization-gen && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "randomization-gen" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Protocol%20Design/randomization-gen into .cursor/skills/randomization-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "randomization-gen", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aipoch/medical-research-skills.git --path 'scientific-skills/Protocol Design/randomization-gen'--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aipoch/medical-research-skills --skill randomization-gen -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aipoch/medical-research-skills randomization-gen --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/'scientific-skills/Protocol Design/randomization-gen' .gemini/skills/randomization-gen && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "randomization-gen" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Protocol%20Design/randomization-gen into .gemini/skills/randomization-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "randomization-gen", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aipoch/medical-research-skills randomization-genInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aipoch/medical-research-skills --skill randomization-gen -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/'scientific-skills/Protocol Design/randomization-gen' .github/skills/randomization-gen && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "randomization-gen" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Protocol%20Design/randomization-gen into .github/skills/randomization-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "randomization-gen", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aipoch/medical-research-skills --skill randomization-gen -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aipoch/medical-research-skills randomization-gen --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/'scientific-skills/Protocol Design/randomization-gen' .opencode/skills/randomization-gen && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "randomization-gen" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Protocol%20Design/randomization-gen into .opencode/skills/randomization-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "randomization-gen", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
randomization-gen- GitHub stars
- 2k
- Token cost
- ~1.5k tokens
- SKILL.md length
- 674 words
- Files
- 6 (incl. scripts, references)
- Skills in repo
- 567
- Repo updated
- First seen
- Licence
- MIT
At a glance
Generates randomization sequences for RCTs including simple, blocked, and stratified allocation.
- Works in 6 steps: Collect parameters: Gather n_subjects… → Validate inputs: Verify n_subjects > 0,… → Checkpoint: Display allocation plan… → …
- Tasks that involve Experimental design
- SKILL.md covers Quick Check, Audit-Ready Commands, When to Use and Workflow, plus 14 more sections
- Runs Python scripts from its folder; calls python
What it does
Randomization Gen is an agent skill from aipoch/medical-research-skills. Generates randomization sequences for RCTs including simple, blocked, and stratified allocation. Produces sealed randomization lists ready for allocation concealment.
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts and reference files (for example `POLISH_CHANGELOG.md`, `eval_report_randomization-gen_result.json` and `references/audit-reference.md`).
It sits in Research & Science, covering Experimental design. The repository describes itself as: Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing. The licence is MIT.
When your agent uses it
- Tasks that involve Experimental design
Example prompts
- “Use the randomization-gen skill to generate randomization sequences for RCTs including simple, blocked, and stratified allocation”
- “/randomization-gen”
Requirements
- Python 3
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Collect parameters: Gather n_subjects (total sample size), n_groups (number of arms), block_size (must be multiple of n_groups), and…
- Validate inputs: Verify n_subjects > 0, n_groups >= 2, block_size is a multiple of n_groups, and n_subjects is divisible by block_size. If…
- Checkpoint: Display allocation plan summary (N per group, block structure, total blocks) to user for confirmation before generating…
- Generate sequence: Create randomization list using blocked randomization. Shuffle block contents using a reproducible seed if provided.
- Output: Return sealed randomization list with block assignments and allocation concealment metadata.
- Fallback: If block_size is not a multiple of n_groups, suggest the nearest valid block sizes and proceed only after user confirmation.
What it can do on your machine
Read from SKILL.md and the folder at commit 686e09d. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Randomization Gen loads about 1.5k tokens when it runs, and up to ~1.6k if it reads all its reference files. Until then it costs about 46 tokens; SKILL.md has 674 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 674 words, ~1,499 tokens.
Download SKILL.mdSave it as
.claude/skills/randomization-gen/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.- name
- randomization-gen
- description
- Generates randomization sequences for RCTs including simple, blocked, and stratified allocation. Produces sealed randomization lists ready for allocation concealment.
- license
- MIT
- author
- AIPOCH
Randomization Gen
RCT randomization table generator.
Quick Check
Use this command to verify that the packaged script entry point can be parsed before deeper execution.
python -m py_compile scripts/main.pyAudit-Ready Commands
Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.
python -m py_compile scripts/main.py
python scripts/main.py --helpWhen to Use
- Use this skill when designing trial randomization, generating allocation sequences, or creating block randomization tables.
- Use this skill when the user says "randomization", "random allocation", "block randomization", "stratified randomization", or "RCT design".
- Use this skill when you need sealed randomization lists ready for allocation concealment.
Workflow
- Collect parameters: Gather n_subjects (total sample size), n_groups (number of arms), block_size (must be multiple of n_groups), and optional stratification factors.
- Validate inputs: Verify n_subjects > 0, n_groups >= 2, block_size is a multiple of n_groups, and n_subjects is divisible by block_size. If invalid, report exact constraint violated and stop.
- Checkpoint: Display allocation plan summary (N per group, block structure, total blocks) to user for confirmation before generating sequence.
- Generate sequence: Create randomization list using blocked randomization. Shuffle block contents using a reproducible seed if provided.
- Output: Return sealed randomization list with block assignments and allocation concealment metadata.
- Fallback: If block_size is not a multiple of n_groups, suggest the nearest valid block sizes and proceed only after user confirmation.
Use Cases
- Clinical trial design
- Animal study randomization
- Blocked randomization
- Stratified allocation
Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
n_subjects | int | Yes | Total sample size |
n_groups | int | Yes | Number of arms/groups |
block_size | int | Yes | Block size (must be multiple of n_groups) |
--output | string | No | Output file path (default: randomization.txt) |
Returns
- Randomization sequence
- Block assignments
- Allocation concealment ready
Example
Input: n=120, 3 groups, block=6 Output: Sealed randomization list
References
- references/audit-reference.md - Supported randomization modes, audit commands, and fallback boundaries
Risk Assessment
| Risk Indicator | Assessment | Level |
|---|---|---|
| Code Execution | Python/R scripts executed locally | Medium |
| Network Access | No external API calls | Low |
| File System Access | Read input files, write output files | Medium |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Output files saved to workspace | Low |
Security Checklist
- No hardcoded credentials or API keys
- No unauthorized file system access (../)
- Output does not expose sensitive information
- Prompt injection protections in place
- Input file paths validated (no ../ traversal)
- Output directory restricted to workspace
- Script execution in sandboxed environment
- Error messages sanitized (no stack traces exposed)
- Dependencies audited
Prerequisites
No additional Python packages required.
Evaluation Criteria
Success Metrics
- Successfully executes main functionality
- Output meets quality standards
- Handles edge cases gracefully
- Performance is acceptable
Show full SKILL.md (266 more words)Show less
Test Cases
- Basic Functionality: Standard input → Expected output
- Edge Case: Invalid input → Graceful error handling
- Performance: Large dataset → Acceptable processing time
Lifecycle Status
- Current Stage: Draft
- Next Review Date: 2026-03-06
- Known Issues: None
- Planned Improvements:
- Performance optimization
- Additional feature support
Output Requirements
Every final response should make these items explicit when they are relevant:
- Objective or requested deliverable
- Inputs used and assumptions introduced
- Workflow or decision path
- Core result, recommendation, or artifact
- Constraints, risks, caveats, or validation needs
- Unresolved items and next-step checks
Error Handling
- If required inputs are missing, state exactly which fields are missing and request only the minimum additional information.
- If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment.
- If
scripts/main.pyfails, report the failure point, summarize what still can be completed safely, and provide a manual fallback. - Do not fabricate files, citations, data, search results, or execution outcomes.
Input Validation
This skill accepts requests that match the documented purpose of randomization-gen and include enough context to complete the workflow safely.
Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:
randomization-genonly handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.
Response Template
Use the following fixed structure for non-trivial requests:
- Objective
- Inputs Received
- Assumptions
- Workflow
- Deliverable
- Risks and Limits
- Next Checks
If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.
© aipoch, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 5 other files (scripts, references) in scientific-skills/Protocol Design/randomization-gen of aipoch/medical-research-skills.
- SKILL.md
- POLISH_CHANGELOG.md
- eval_report_randomization-gen_result.json
- randomization.csv
- references/audit-reference.md
- scripts/main.py
Open the folder on GitHubat commit 686e09d
Compare with similar skills
Randomization Gen next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Randomization Gen this skillaipoch/medical-research-skills | 2k | — | ~1.5k | Automated safety check: Pass | MIT | |
| Scientific Critical Thinkingweapp-tailwindcss/weapp-tailwindcss | 1.9k | 23 repos | ~5.9k | Automated safety check: Notes | MIT | |
| Claim-Driven Experiment PlannerzjYao36/Auto-Research-Refine | 128 | 7 repos | ~2.3k | Automated safety check: Notes | None | |
| Benchmark Paper TemplateHKUSTDial/Supervisor-Skills | 8.5k | — | ~2.8k | Automated safety check: Pass | CC-BY-4.0 | |
| Research Refine PipelinezjYao36/Auto-Research-Refine | 128 | 6 repos | ~1.4k | Automated safety check: Notes | None | |
| Metabolic Study Planneraiming-lab/AutoResearchClaw | 15k | — | ~1.9k | Automated safety check: Pass | MIT |
Similar skills
Claim-Driven Experiment Planner
zjYao36/Auto-Research-Refine
Turns a refined research proposal into a claim-to-evidence-to-run-order roadmap instead of a sprawling benchmark wishlist.
Benchmark Paper Template
HKUSTDial/Supervisor-Skills
Structures benchmark and evaluation papers around five pillars, with a completeness audit, an Introduction logic chain, a section skeleton and a pre-submission checklist.
Research Refine Pipeline
zjYao36/Auto-Research-Refine
Chains research-refine and experiment-plan to turn a vague research direction into a focused proposal and a claim-driven experiment roadmap.
Metabolic Study Planner
aiming-lab/AutoResearchClaw
Turns a broad metabolic modelling topic into a concrete, paper-shaped plan with organism, model, perturbations, metrics and figures before any FBA code is written.
Experimental Design
Oleafly/Oleafly
Design experiments and studies BEFORE data is collected — choosing a design, randomizing, blocking, and laying out treatment combinations so results are interpretable.
More from aipoch/medical-research-skills
All 567 skills in this repoAcademic Poster Generator
aipoch/medical-research-skills
Complete workflow for generating academic research posters from PDF literature; use when you need to extract paper content from PDFs and produce a LaTeX-based poster…
Diagnostic Study Quality Assessment Quadas
aipoch/medical-research-skills
Analyzes clinical diagnostic accuracy studies for bias using the QUADAS-2 tool.
Exploratory Data Analysis
aipoch/medical-research-skills
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats.
Iso Certification
aipoch/medical-research-skills
A toolkit for preparing ISO 13485:2016 certification documentation for medical device QMS.
Journal Skills
aipoch/medical-research-skills
Recommends target journals for manuscript submission by analyzing the paper topic/abstract and the journal distribution of similar PubMed literature; use when users ask for journal…
Latex Posters
aipoch/medical-research-skills
Creates academic-poster writing packages for LaTeX using beamerposter, tikzposter, or baposter.
Related
Categories
Questions about Randomization Gen
What does Randomization Gen do?
Generates randomization sequences for RCTs including simple, blocked, and stratified allocation. Randomization Gen is an agent skill from aipoch/medical-research-skills. Generates randomization sequences for RCTs including simple, blocked, and stratified allocation.
When should I use Randomization Gen?
Randomization Gen fits situations like: tasks that involve Experimental design.
How do I install Randomization Gen in Claude Code?
Run `npx skills add aipoch/medical-research-skills --skill randomization-gen -a claude-code`. Or copy the skill folder (scientific-skills/Protocol Design/randomization-gen in aipoch/medical-research-skills) into .claude/skills/randomization-gen in your project. Claude Code loads it when a task matches its description.
How do I install Randomization Gen in Codex?
Run `npx skills add aipoch/medical-research-skills --skill randomization-gen -a codex`. Or copy the skill folder (scientific-skills/Protocol Design/randomization-gen in aipoch/medical-research-skills) into .agents/skills/randomization-gen in your project. Codex loads it when a task matches its description.
Can I use Randomization Gen in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aipoch/medical-research-skills --skill randomization-gen -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/randomization-gen, .gemini/skills/randomization-gen, .github/skills/randomization-gen and .opencode/skills/randomization-gen in your project.
What does Randomization Gen need to run?
Going by SKILL.md and its folder, Randomization Gen needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Randomization Gen access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Randomization Gen safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Randomization Gen use?
Randomization Gen is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Randomization Gen use?
About 1.5k tokens (SKILL.md is roughly 6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 121 tokens, read only when the agent opens those files.
What are the alternatives to Randomization Gen?
Skills that share tags, products or a category with Randomization Gen: Scientific Critical Thinking (weapp-tailwindcss/weapp-tailwindcss, 1.9k stars), Claim-Driven Experiment Planner (zjYao36/Auto-Research-Refine, 128 stars), Benchmark Paper Template (HKUSTDial/Supervisor-Skills, 8.5k stars) and Research Refine Pipeline (zjYao36/Auto-Research-Refine, 128 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Randomization Gen?
aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,974 GitHub stars. The repository holds 567 skills in this directory. The repository was last updated on September 17, 2026.
Source: aipoch/medical-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.